IBM hope to ease commutes with traffic predicting algorithm

Get into a taxi and it's safe to assume the driver knows the
ins, outs, shortcuts and potential traffic tie-ups between you and
your destination. That kind of knowledge comes from years of
experience, and IBM is taking a similar tact that blends real-time
data and historical information into a new breed of traffic
prediction.

IBM is testing the new traffic management technology in a pilot
programme in Lyon, France, that's designed to provide the city's
transportation engineers with "real-time decision support" so they
can proactively reduce congestion. Called Decision Support System
Optimiser (DSSO), the technology uses IBM's Data Expansion
Algorithm to combine old and new data to predict future traffic
flow. Over time the system "learns" from successful outcomes to
fine-tune future recommendations.

The company's technology allows traffic engineers to quickly
take action based on constantly updated information, such as
putting detours in place or providing alternative routes to get
traffic moving after a snag. They're unable to do this now,
according to IBM, since most metro traffic management centres rely
only on video feeds and colour maps showing real-time traffic
conditions. Jurij R. Paraszczak, director of Smarter
Cities IBM Research, says this means traffic engineers don't
have a "360-degree view" of traffic, and depending on predefined
responses or making reactive decisions, they don't always fully
take into account all current and future patterns.

"Rather than pulling all the data together and displaying it in
one place where people make decisions on to what to do with it, the
idea is to pull the data, display it and then provide tools to
drive what-ifs," Paraszczak told Wired.com. "The idea is to help
them make decisions."

DSSO takes into account not only a city's current, historical
and predicted future traffic patterns, but it also fills in the
blanks where information doesn't exist. "In areas where there's not
as much data as you'd like to do a statistical measurement," adds
Paraszczak, "we build a flow model that connects to the area we do
know well. Based on these statistics, we'll provide a prediction as
to what traffic volume to expect."

When an incident occurs, DSSO allows traffic engineers to
analyse different scenarios on how to resolve the problem and
predicts the outcome of, say, adjusting traffic signals, opening up
another lane and routing traffic using statistical analysis.

IBM unveiled the technology at Smart City Expo and World
Congress in Barcelona last week. Paraszczak can't say when
(or even if) the pilot will be extended to more cities, but he
noted that IBM believes the technology is ready for drive-time and
plans to prove it on Lyon's roads. "There're many ways to go to
market," Paraszczak says, "but testing it in the marketplace is the
best way."